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  1. as_float_array — scikit-learn 1.5.2 documentation

    Skip to main content Back to top Ctrl + K GitHub as_float_array # sklearn.utils. as_float_array ( X , * , copy = True...
    scikit-learn.org/stable/modules/generated/sklearn.utils.as_float_array.html
    Sat Nov 23 04:49:14 UTC 2024
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  2. type_of_target — scikit-learn 1.5.2 documentation

    Skip to main content Back to top Ctrl + K GitHub type_of_target # sklearn.utils.multiclass. type_of_target ( y , inpu...
    scikit-learn.org/stable/modules/generated/sklearn.utils.multiclass.type_of_target.html
    Sat Nov 23 04:49:14 UTC 2024
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  3. column_or_1d — scikit-learn 1.5.2 documentation

    Skip to main content Back to top Ctrl + K GitHub column_or_1d # sklearn.utils.validation. column_or_1d ( y , * , dtyp...
    scikit-learn.org/stable/modules/generated/sklearn.utils.validation.column_or_1d.html
    Sat Nov 23 04:49:15 UTC 2024
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  4. Demo of HDBSCAN clustering algorithm — scikit-l...

    In this demo we will take a look at cluster.HDBSCAN from the perspective of generalizing the cluster.DBSCAN algorithm. We’ll compare both algorithms on specific datasets. Finally we’ll evaluate HDB...
    scikit-learn.org/stable/auto_examples/cluster/plot_hdbscan.html
    Sat Nov 23 04:49:14 UTC 2024
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  5. Sparse coding with a precomputed dictionary — s...

    Transform a signal as a sparse combination of Ricker wavelets. This example visually compares different sparse coding methods using the SparseCoder estimator. The Ricker (also known as Mexican hat ...
    scikit-learn.org/stable/auto_examples/decomposition/plot_sparse_coding.html
    Sat Nov 23 04:49:16 UTC 2024
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  6. Multi-dimensional scaling — scikit-learn 1.5.2 ...

    An illustration of the metric and non-metric MDS on generated noisy data. The reconstructed points using the metric MDS and non metric MDS are slightly shifted to avoid overlapping. Total running t...
    scikit-learn.org/stable/auto_examples/manifold/plot_mds.html
    Sat Nov 23 04:49:16 UTC 2024
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  7. Density Estimation for a Gaussian mixture — sci...

    Plot the density estimation of a mixture of two Gaussians. Data is generated from two Gaussians with different centers and covariance matrices. Total running time of the script:(0 minutes 0.160 sec...
    scikit-learn.org/stable/auto_examples/mixture/plot_gmm_pdf.html
    Sat Nov 23 04:49:15 UTC 2024
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  8. Lasso on dense and sparse data — scikit-learn 1...

    We show that linear_model.Lasso provides the same results for dense and sparse data and that in the case of sparse data the speed is improved. Comparing the two Lasso implementations on Dense data:...
    scikit-learn.org/stable/auto_examples/linear_model/plot_lasso_dense_vs_sparse_data.html
    Sat Nov 23 04:49:15 UTC 2024
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  9. Map data to a normal distribution — scikit-lear...

    This example demonstrates the use of the Box-Cox and Yeo-Johnson transforms through PowerTransformer to map data from various distributions to a normal distribution. The power transform is useful a...
    scikit-learn.org/stable/auto_examples/preprocessing/plot_map_data_to_normal.html
    Sat Nov 23 04:49:15 UTC 2024
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  10. Neighborhood Components Analysis Illustration —...

    This example illustrates a learned distance metric that maximizes the nearest neighbors classification accuracy. It provides a visual representation of this metric compared to the original point sp...
    scikit-learn.org/stable/auto_examples/neighbors/plot_nca_illustration.html
    Sat Nov 23 04:49:14 UTC 2024
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